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  • Total Questions: 322
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Databricks Databricks-Certified-Data-Engineer-Associate Exam Syllabus Topics:

TopicDetails
Topic 1
  • Incremental Data Processing: In this topic questions about identifying Delta Lake, benefits of ACID transactions, a scenario to use an external table, location of a table, the benefits of Zordering, the kind of files, CTAS as a solution, the impact of ON VIOLATION DROP ROW and ON VIOLATION FAIL UPDATE, and the necessary component to create a new DLT pipeline. Moreover, the topic also discusses directory structure of Delta Lake files, generated column, adding a table comment, and the benefits of the MERGE command.
Topic 2
  • Databricks Lakehouse Platform: This topic covers the relationship between the data lakehouse and the data warehouse, the improvement in data quality, comparing and contrasting silver and gold tables, elements of the Databricks Platform Architecture, and differentiating between all-purpose clusters and jobs clusters. Moreover, it identifies how cluster software is versioned, how clusters can be filtered, how to use multiple languages, how to run one notebook, how notebooks can be shared, Git operations, and limitations in Databricks Notebooks. Lastly, the topic describes how clusters are terminated, how to use multiple languages, and how Databricks Repos enables CI
  • CD workflows.
Topic 3
  • Data Governance: It identifies one of the four areas of data governance, Unity Catalog securables, and the cluster security modes. It also discusses how to create a UC-enabled all-purpose cluster and a DBSQL warehouse. The topic explains how to implement data object access control, create a DBSQL warehouse, and e a UC-enabled all-purpose cluster.
Topic 4
  • Production Pipelines: It focuses on identifying the advantages of using multiple tasks in Jobs, a suitable scenario where predecessor task should be set up, CRON as an opportunity for scheduling opportunity, and how an alert can be sent via email. The topic also discusses setting up a predecessor task in Jobs, reviewing a task's execution history, and debugging a failed task. Lastly, it delves into setting up a retry policy in case of failure and creating an alert in the case of a failed task.
Topic 5
  • ELT with Apache Spark: It focuses on extracting data, identifying the prefix, creating a view, duplicating rows, creating a new table, utilizing the dot, parsing JSON, and defining a SQL UDF. Moreover, the topic delves into describing the security model, identifying the location of a function, and identifying the PIVOT.

Reference: https://www.databricks.com/learn/certification/data-engineer-associate

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Databricks Certified Data Engineer Associate Sample Questions:

A data engineer needs to use a Delta table as part of a data pipeline, but they do not know if they have the appropriate permissions.
In which of the following locations can the data engineer review their permissions on the table?

  • A. Databricks Filesystem
  • B. Dashboards
  • C. Data Explorer
  • D. Repos
  • E. Jobs
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

Which of the following commands will return the number of null values in the member_id column?

  • A. SELECT count(member_id) FROM my_table;
  • B. SELECT count_if(member_id IS NULL) FROM my_table;
  • C. SELECT null(member_id) FROM my_table;
  • D. SELECT count_null(member_id) FROM my_table;
  • E. SELECT count(member_id) - count_null(member_id) FROM my_table;
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

What is the functionality of AutoLoader in Databricks?

  • A. Auto Loader automatically ingests and processes new files from cloud storage, handling both batch and streaming data with support for schema evolution.
  • B. Auto Loader automatically ingests and processes new files from cloud storage, handling only streaming data with no support for schema evolution.
  • C. Auto Loader automatically ingests and processes new files from cloud storage, handling batch data with support for schema evolution.
  • D. Auto Loader automatically ingests and processes new files from cloud storage, handling batch and streaming data with no support for schema evolution.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Explanation: Only visible for Pass4Leader members. You can sign-up / login (it's free).

A data engineer is setting up access control in Unity Catalog and needs to ensure that a group of data analysts can query tables but not modify data. Which permission should the data engineer grant to the data analysts?

  • A. INSERT
  • B. MODIFY
  • C. ALL PRIVILEGES
  • D. SELECT
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

Explanation: Only visible for Pass4Leader members. You can sign-up / login (it's free).

A data engineer has a Python variable table_name that they would like to use in a SQL query.
They want to construct a Python code block that will run the query using table_name.
They have the following incomplete code block:
____(f"SELECT customer_id, spend FROM {table_name}")
Which of the following can be used to fill in the blank to successfully complete the task?

  • A. spark.table
  • B. spark.delta.sql
  • C. spark.sql
  • D. dbutils.sql
  • E. spark.delta.table
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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